Eryildirim, A.Çetin, A. Enis2016-02-082016-02-082009-05http://hdl.handle.net/11693/26737Date of Conference: 4-8 May 2009Conference name: 2009 IEEE Radar ConferenceIn this paper, a novel descriptive feature parameter extraction method from Synthetic Aperture Radar (SAR) images is proposed. The new method is based on the two-dimensional (2-D) real cepstrum. This novel 2-D cepstrum method is compared with principal component analysis (PCA) method by testing over the MSTAR image database. The extracted features are classified using Support Vector Machine (SVM). We demonstrate that discrimination of natural background (clutter) and man-made objects (metal objects) in SAR imagery is possible using the 2-D cepstrum feature parameters. In addition, the computational cost of the cepstrum method is lower than the PCA method. Experimental results are presented. ©2009 IEEE.EnglishCepstrumCepstrum methodComputational costsFeature parametersImage databaseMan made objectsNatural backgroundsPCA methodSAR imagerySAR ImagesSynthetic aperture radar imagesFeature extractionImage retrievalImaging systemsMetal recoveryObject recognitionParameter extractionPrincipal component analysisSmeltingSupport vector machinesSynthetic aperturesSynthetic aperture radarConference Paper10.1109/RADAR.2009.4976990